Intelligence Classification of the Timetable Problem: A Memetic Approach

Eboka Andrew Okonji; Yerokun Mary Oluwatoyin; Okoba Ifeoma Patricia

doi:doi:10.11648/j.ijdst.20170302.12

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Intelligence Classification of the Timetable Problem: A Memetic Approach

Eboka Andrew Okonji, Yerokun Mary Oluwatoyin, Okoba Ifeoma Patricia

Published in International Journal on Data Science and Technology (Volume 3, Issue 2)

Received: 5 April 2017 Accepted: 15 May 2017 Published: 27 July 2017

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Abstract

Scheduling tasks persist in our daily functioning and as academia, abounds more in University circle as hard-NP constraint satisfaction tasks. Many studies exist with the objective of resolving the many conflicted constraints that exists in a timetable schedule using various algorithms. Many of such algorithms simply search the domain space for a goal state that satisfies the problem constraints. Our study yields an outcome assignment that provides a complete, feasible and optimal academic schedule that satisfies medium cum hard constraints for the Federal University of Petroleum Resource Effurun in Delta State of Nigeria using memetic algorithm. Results showed that model converges after 4minutes and 29seconds; while its convergence time depends on use of belief space to ensure agents do not violate model bounds, encoding scheme used amongst others. The schedule considers both instructors and students’ preference as medium constraints of high priority.

Published in	International Journal on Data Science and Technology (Volume 3, Issue 2)
DOI	10.11648/j.ijdst.20170302.12
Page(s)	24-33
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Fitness, Constraints, Cross-Over, Mutation, Timetable, Memetic Algorithm, Intelligent, Schedule

References

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APA Style

Eboka Andrew Okonji, Yerokun Mary Oluwatoyin, Okoba Ifeoma Patricia. (2017). Intelligence Classification of the Timetable Problem: A Memetic Approach. International Journal on Data Science and Technology, 3(2), 24-33. https://doi.org/10.11648/j.ijdst.20170302.12

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ACS Style

Eboka Andrew Okonji; Yerokun Mary Oluwatoyin; Okoba Ifeoma Patricia. Intelligence Classification of the Timetable Problem: A Memetic Approach. Int. J. Data Sci. Technol. 2017, 3(2), 24-33. doi: 10.11648/j.ijdst.20170302.12

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AMA Style

Eboka Andrew Okonji, Yerokun Mary Oluwatoyin, Okoba Ifeoma Patricia. Intelligence Classification of the Timetable Problem: A Memetic Approach. Int J Data Sci Technol. 2017;3(2):24-33. doi: 10.11648/j.ijdst.20170302.12

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@article{10.11648/j.ijdst.20170302.12,
  author = {Eboka Andrew Okonji and Yerokun Mary Oluwatoyin and Okoba Ifeoma Patricia},
  title = {Intelligence Classification of the Timetable Problem: A Memetic Approach},
  journal = {International Journal on Data Science and Technology},
  volume = {3},
  number = {2},
  pages = {24-33},
  doi = {10.11648/j.ijdst.20170302.12},
  url = {https://doi.org/10.11648/j.ijdst.20170302.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdst.20170302.12},
  abstract = {Scheduling tasks persist in our daily functioning and as academia, abounds more in University circle as hard-NP constraint satisfaction tasks. Many studies exist with the objective of resolving the many conflicted constraints that exists in a timetable schedule using various algorithms. Many of such algorithms simply search the domain space for a goal state that satisfies the problem constraints. Our study yields an outcome assignment that provides a complete, feasible and optimal academic schedule that satisfies medium cum hard constraints for the Federal University of Petroleum Resource Effurun in Delta State of Nigeria using memetic algorithm. Results showed that model converges after 4minutes and 29seconds; while its convergence time depends on use of belief space to ensure agents do not violate model bounds, encoding scheme used amongst others. The schedule considers both instructors and students’ preference as medium constraints of high priority.},
 year = {2017}
}

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TY  - JOUR
T1  - Intelligence Classification of the Timetable Problem: A Memetic Approach
AU  - Eboka Andrew Okonji
AU  - Yerokun Mary Oluwatoyin
AU  - Okoba Ifeoma Patricia
Y1  - 2017/07/27
PY  - 2017
N1  - https://doi.org/10.11648/j.ijdst.20170302.12
DO  - 10.11648/j.ijdst.20170302.12
T2  - International Journal on Data Science and Technology
JF  - International Journal on Data Science and Technology
JO  - International Journal on Data Science and Technology
SP  - 24
EP  - 33
PB  - Science Publishing Group
SN  - 2472-2235
UR  - https://doi.org/10.11648/j.ijdst.20170302.12
AB  - Scheduling tasks persist in our daily functioning and as academia, abounds more in University circle as hard-NP constraint satisfaction tasks. Many studies exist with the objective of resolving the many conflicted constraints that exists in a timetable schedule using various algorithms. Many of such algorithms simply search the domain space for a goal state that satisfies the problem constraints. Our study yields an outcome assignment that provides a complete, feasible and optimal academic schedule that satisfies medium cum hard constraints for the Federal University of Petroleum Resource Effurun in Delta State of Nigeria using memetic algorithm. Results showed that model converges after 4minutes and 29seconds; while its convergence time depends on use of belief space to ensure agents do not violate model bounds, encoding scheme used amongst others. The schedule considers both instructors and students’ preference as medium constraints of high priority.
VL  - 3
IS  - 2
ER  -

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Author Information

Eboka Andrew Okonji

Department of Computer Education, Federal College of Education Technical, Asaba, Nigeria
Yerokun Mary Oluwatoyin

Department of Computer Education, Federal College of Education Technical, Asaba, Nigeria
Okoba Ifeoma Patricia

Department of Computer Education, Federal College of Education Technical, Asaba, Nigeria

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Plain Text BibTeX RIS

APA Style

Eboka Andrew Okonji, Yerokun Mary Oluwatoyin, Okoba Ifeoma Patricia. (2017). Intelligence Classification of the Timetable Problem: A Memetic Approach. International Journal on Data Science and Technology, 3(2), 24-33. https://doi.org/10.11648/j.ijdst.20170302.12

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ACS Style

Eboka Andrew Okonji; Yerokun Mary Oluwatoyin; Okoba Ifeoma Patricia. Intelligence Classification of the Timetable Problem: A Memetic Approach. Int. J. Data Sci. Technol. 2017, 3(2), 24-33. doi: 10.11648/j.ijdst.20170302.12

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AMA Style

Eboka Andrew Okonji, Yerokun Mary Oluwatoyin, Okoba Ifeoma Patricia. Intelligence Classification of the Timetable Problem: A Memetic Approach. Int J Data Sci Technol. 2017;3(2):24-33. doi: 10.11648/j.ijdst.20170302.12

Copy | Download

@article{10.11648/j.ijdst.20170302.12,
  author = {Eboka Andrew Okonji and Yerokun Mary Oluwatoyin and Okoba Ifeoma Patricia},
  title = {Intelligence Classification of the Timetable Problem: A Memetic Approach},
  journal = {International Journal on Data Science and Technology},
  volume = {3},
  number = {2},
  pages = {24-33},
  doi = {10.11648/j.ijdst.20170302.12},
  url = {https://doi.org/10.11648/j.ijdst.20170302.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdst.20170302.12},
  abstract = {Scheduling tasks persist in our daily functioning and as academia, abounds more in University circle as hard-NP constraint satisfaction tasks. Many studies exist with the objective of resolving the many conflicted constraints that exists in a timetable schedule using various algorithms. Many of such algorithms simply search the domain space for a goal state that satisfies the problem constraints. Our study yields an outcome assignment that provides a complete, feasible and optimal academic schedule that satisfies medium cum hard constraints for the Federal University of Petroleum Resource Effurun in Delta State of Nigeria using memetic algorithm. Results showed that model converges after 4minutes and 29seconds; while its convergence time depends on use of belief space to ensure agents do not violate model bounds, encoding scheme used amongst others. The schedule considers both instructors and students’ preference as medium constraints of high priority.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Intelligence Classification of the Timetable Problem: A Memetic Approach
AU  - Eboka Andrew Okonji
AU  - Yerokun Mary Oluwatoyin
AU  - Okoba Ifeoma Patricia
Y1  - 2017/07/27
PY  - 2017
N1  - https://doi.org/10.11648/j.ijdst.20170302.12
DO  - 10.11648/j.ijdst.20170302.12
T2  - International Journal on Data Science and Technology
JF  - International Journal on Data Science and Technology
JO  - International Journal on Data Science and Technology
SP  - 24
EP  - 33
PB  - Science Publishing Group
SN  - 2472-2235
UR  - https://doi.org/10.11648/j.ijdst.20170302.12
AB  - Scheduling tasks persist in our daily functioning and as academia, abounds more in University circle as hard-NP constraint satisfaction tasks. Many studies exist with the objective of resolving the many conflicted constraints that exists in a timetable schedule using various algorithms. Many of such algorithms simply search the domain space for a goal state that satisfies the problem constraints. Our study yields an outcome assignment that provides a complete, feasible and optimal academic schedule that satisfies medium cum hard constraints for the Federal University of Petroleum Resource Effurun in Delta State of Nigeria using memetic algorithm. Results showed that model converges after 4minutes and 29seconds; while its convergence time depends on use of belief space to ensure agents do not violate model bounds, encoding scheme used amongst others. The schedule considers both instructors and students’ preference as medium constraints of high priority.
VL  - 3
IS  - 2
ER  -

Copy | Download